
where the query rewriter \(\text{NLG}(\theta )\)  is often implemented using a Transformer-based auto-regressive language model, parameterized by \(\theta \) .
For example, [1]} propose to use a fine-tuned GPT-2 model [2]} for query rewriting as
\(\hat{Q}_i &= \text{GPT-2}(\texttt {[CLS]} \circ Q_1 \circ \texttt {[SEP]} \circ Q_2 ; \texttt {[SEP]}....\texttt {[SEP]}Q_{i} \circ \texttt {[GO]}),\) 
